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Clinical Characteristics of 18 Patients with Psoriasis and Multiple Myeloma Identified Through Digital Health Crowdsourcing
Psoriasis is a skin condition that affects over 100 million people worldwide, while multiple myeloma (MM) accounts for 10% of all hematologic malignancies in the US. There has been limited research on the intersection of psoriasis and MM, and clinicians often face difficult decisions in treating pat...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Springer Healthcare
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7367969/ https://www.ncbi.nlm.nih.gov/pubmed/32638223 http://dx.doi.org/10.1007/s13555-020-00416-5 |
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author | Jin, Joy Q. Ahlstrom, Jenny M. Sweeney, Nathan W. Liao, Wilson |
author_facet | Jin, Joy Q. Ahlstrom, Jenny M. Sweeney, Nathan W. Liao, Wilson |
author_sort | Jin, Joy Q. |
collection | PubMed |
description | Psoriasis is a skin condition that affects over 100 million people worldwide, while multiple myeloma (MM) accounts for 10% of all hematologic malignancies in the US. There has been limited research on the intersection of psoriasis and MM, and clinicians often face difficult decisions in treating patients diagnosed with both conditions. For instance, the management of psoriasis with systemic immunotherapies in MM patients can be challenging because of concern about immunosuppression and possible worsening of MM. Online crowdsourcing platforms have recently become innovative tools that can actively empower patients in scientific research by enabling the contribution of health data. One such platform, HealthTree(®), helps MM patients find optimal myeloma treatments and has registered > 6000 patients, many of whom have uploaded medical records and genetic profiles. By taking advantage of patient health data available on HealthTree, researchers can gain a greater understanding of the clinical characteristics and treatment responses of patients diagnosed with psoriasis and MM. In this case series, we first report a psoriasis and MM patient treated with the IL-17 inhibitor ixekizumab who demonstrated a temporary, 2-month improvement in MM biomarkers (M-protein, kappa, and kappa:lambda ratio). We then report on the clinical characteristics of 18 patients with verified profiles on HealthTree indicating concurrent psoriasis and MM conditions. We surveyed gender, age, psoriasis type, psoriasis treatment history, myeloma type, myeloma genetic features, and myeloma association with bone damage, hypercalcemia, or osteopenia. Four patients were treated with systemic immunomodulators for psoriasis, with responses suggesting that these therapies did not worsen MM progression. Our results validate crowdsourcing as a way to assess patient demographics and treatment responses for use in dermatology research. We examine the demographics of patients diagnosed with psoriasis and MM and investigate the use of systemic immunomodulators for treatment of psoriasis in MM patients. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s13555-020-00416-5) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-7367969 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Springer Healthcare |
record_format | MEDLINE/PubMed |
spelling | pubmed-73679692020-07-22 Clinical Characteristics of 18 Patients with Psoriasis and Multiple Myeloma Identified Through Digital Health Crowdsourcing Jin, Joy Q. Ahlstrom, Jenny M. Sweeney, Nathan W. Liao, Wilson Dermatol Ther (Heidelb) Case Series Psoriasis is a skin condition that affects over 100 million people worldwide, while multiple myeloma (MM) accounts for 10% of all hematologic malignancies in the US. There has been limited research on the intersection of psoriasis and MM, and clinicians often face difficult decisions in treating patients diagnosed with both conditions. For instance, the management of psoriasis with systemic immunotherapies in MM patients can be challenging because of concern about immunosuppression and possible worsening of MM. Online crowdsourcing platforms have recently become innovative tools that can actively empower patients in scientific research by enabling the contribution of health data. One such platform, HealthTree(®), helps MM patients find optimal myeloma treatments and has registered > 6000 patients, many of whom have uploaded medical records and genetic profiles. By taking advantage of patient health data available on HealthTree, researchers can gain a greater understanding of the clinical characteristics and treatment responses of patients diagnosed with psoriasis and MM. In this case series, we first report a psoriasis and MM patient treated with the IL-17 inhibitor ixekizumab who demonstrated a temporary, 2-month improvement in MM biomarkers (M-protein, kappa, and kappa:lambda ratio). We then report on the clinical characteristics of 18 patients with verified profiles on HealthTree indicating concurrent psoriasis and MM conditions. We surveyed gender, age, psoriasis type, psoriasis treatment history, myeloma type, myeloma genetic features, and myeloma association with bone damage, hypercalcemia, or osteopenia. Four patients were treated with systemic immunomodulators for psoriasis, with responses suggesting that these therapies did not worsen MM progression. Our results validate crowdsourcing as a way to assess patient demographics and treatment responses for use in dermatology research. We examine the demographics of patients diagnosed with psoriasis and MM and investigate the use of systemic immunomodulators for treatment of psoriasis in MM patients. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s13555-020-00416-5) contains supplementary material, which is available to authorized users. Springer Healthcare 2020-07-07 /pmc/articles/PMC7367969/ /pubmed/32638223 http://dx.doi.org/10.1007/s13555-020-00416-5 Text en © The Author(s) 2020 https://creativecommons.org/licenses/by-nc/4.0/This article is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License, which permits any non-commercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) . |
spellingShingle | Case Series Jin, Joy Q. Ahlstrom, Jenny M. Sweeney, Nathan W. Liao, Wilson Clinical Characteristics of 18 Patients with Psoriasis and Multiple Myeloma Identified Through Digital Health Crowdsourcing |
title | Clinical Characteristics of 18 Patients with Psoriasis and Multiple Myeloma Identified Through Digital Health Crowdsourcing |
title_full | Clinical Characteristics of 18 Patients with Psoriasis and Multiple Myeloma Identified Through Digital Health Crowdsourcing |
title_fullStr | Clinical Characteristics of 18 Patients with Psoriasis and Multiple Myeloma Identified Through Digital Health Crowdsourcing |
title_full_unstemmed | Clinical Characteristics of 18 Patients with Psoriasis and Multiple Myeloma Identified Through Digital Health Crowdsourcing |
title_short | Clinical Characteristics of 18 Patients with Psoriasis and Multiple Myeloma Identified Through Digital Health Crowdsourcing |
title_sort | clinical characteristics of 18 patients with psoriasis and multiple myeloma identified through digital health crowdsourcing |
topic | Case Series |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7367969/ https://www.ncbi.nlm.nih.gov/pubmed/32638223 http://dx.doi.org/10.1007/s13555-020-00416-5 |
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